Comments (3)
Experiments:
Current machine, full load time
julia -e 'tic(); using PDMP; toc()'
elapsed time: 7.926201809 seconds
This is outrageous. Chasing the culprit.
In PDMP.jl
:
using Compat
using Klara.ess
using ApproxFun
using Polynomials:
Poly,
roots,
polyint,
polyval
julia -e 'tic(); using Compat; toc()'
elapsed time: 0.047637768 seconds
Negligible
julia -e 'tic(); using Klara.ess; toc()'
elapsed time: 1.290301332 seconds
That's pretty bad
julia -e 'tic(); using ApproxFun; toc()'
elapsed time: 6.580165969 seconds
That's downright awful.
julia -e 'tic(); using Polynomials; toc()'
elapsed time: 0.062788019 seconds
Negligible again.
from pdsampler.jl.
Removing dependencies
- removing
Klara.ess
- removing
Distributions:Beta
- removing
ApproxFun
julia -e 'tic(); using PDMP; toc()'
elapsed time: 1.567161443 seconds
from pdsampler.jl.
More informations:
- in Julia 0.5.2 it's half that time (changing Readme to reflect that for now recommended to use Julia 0.5.2 as a result)
- apparently the problem is partly known as per JuliaLang/julia#21173
from pdsampler.jl.
Related Issues (20)
- Extend path integral of polynomials for local BPS HOT 1
- investigate multiple core usage for the local BPS HOT 7
- Hide functions that do not strictly need to be exposed HOT 1
- Add switch for multithreading and test resulting performances HOT 2
- Testing script Azure HOT 4
- Use Compat library to help with forward looking language HOT 5
- Fix evaluation of gradient in Global/Local BPS HOT 1
- GBPS for local BPS
- Restricted GBPS
- Julia 0.5.0 line break models/pmf/#36 HOT 1
- add shortcut for spherical gaussians
- Naming? HOT 9
- registering package HOT 2
- Read and integrate R-code
- Remove Klara dependency HOT 1
- v06 compat HOT 1
- Julia 0.6.3 & 0.7-alpha compat HOT 4
- Move this repo to the `JuliaAI` organization? HOT 1
- The number of dimensions of the algorithm is independent of the amount or size of the data analyzed.
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from pdsampler.jl.